Zobrazeno 1 - 10
of 8 676
pro vyhledávání: '"Yoon, Hee"'
Autor:
Yoon, Hee Suk, Yoon, Eunseop, Tee, Joshua Tian Jin, Zhang, Kang, Heo, Yu-Jung, Chang, Du-Seong, Yoo, Chang D.
Multimodal Dialogue Response Generation (MDRG) is a recently proposed task where the model needs to generate responses in texts, images, or a blend of both based on the dialogue context. Due to the lack of a large-scale dataset specifically for this
Externí odkaz:
http://arxiv.org/abs/2408.05926
Test-Time Adaptation (TTA) has emerged as a crucial solution to the domain shift challenge, wherein the target environment diverges from the original training environment. A prime exemplification is TTA for Automatic Speech Recognition (ASR), which e
Externí odkaz:
http://arxiv.org/abs/2408.05769
Autor:
Yoon, Eunseop, Yoon, Hee Suk, Eom, SooHwan, Han, Gunsoo, Nam, Daniel Wontae, Jo, Daejin, On, Kyoung-Woon, Hasegawa-Johnson, Mark A., Kim, Sungwoong, Yoo, Chang D.
Reinforcement Learning from Human Feedback (RLHF) leverages human preference data to train language models to align more closely with human essence. These human preference data, however, are labeled at the sequence level, creating a mismatch between
Externí odkaz:
http://arxiv.org/abs/2407.16574
Autor:
Yoon, Hee Suk, Yoon, Eunseop, Tee, Joshua Tian Jin, Hasegawa-Johnson, Mark, Li, Yingzhen, Yoo, Chang D.
In deep learning, test-time adaptation has gained attention as a method for model fine-tuning without the need for labeled data. A prime exemplification is the recently proposed test-time prompt tuning for large-scale vision-language models such as C
Externí odkaz:
http://arxiv.org/abs/2403.14119
Autor:
Eom, SooHwan, Yoon, Eunseop, Yoon, Hee Suk, Kim, Chanwoo, Hasegawa-Johnson, Mark, Yoo, Chang D.
In Automatic Speech Recognition (ASR) systems, a recurring obstacle is the generation of narrowly focused output distributions. This phenomenon emerges as a side effect of Connectionist Temporal Classification (CTC), a robust sequence learning tool t
Externí odkaz:
http://arxiv.org/abs/2403.11578
Autor:
Yoon, Sunyoung, Kim, Taerim, Roh, Taehwan, Chang, Hansol, Hwang, Sung Yeon, Yoon, Hee, Shin, Tae Gun, Sim, Min Seob, Jo, Ik Joon, Cha, Won Chul
Publikováno v:
JMIR mHealth and uHealth, Vol 9, Iss 4, p e24142 (2021)
BackgroundCardiovascular disease is the leading cause of death worldwide. Early recognition, diagnosis, and reperfusion are the key elements of treatment for ST-segment elevation myocardial infarction. The absence of a prehospital 12-lead electrocard
Externí odkaz:
https://doaj.org/article/6231e648c6c746e68bdb477d6d728a80
Video-grounded Dialogue (VGD) aims to answer questions regarding a given multi-modal input comprising video, audio, and dialogue history. Although there have been numerous efforts in developing VGD systems to improve the quality of their responses, e
Externí odkaz:
http://arxiv.org/abs/2312.09736
Data augmentation is a crucial component in training neural networks to overcome the limitation imposed by data size, and several techniques have been studied for time series. Although these techniques are effective in certain tasks, they have yet to
Externí odkaz:
http://arxiv.org/abs/2312.05790
Autor:
Yoo, Junsang, Jung, Kwang Yul, Kim, Taerim, Lee, Taerim, Hwang, Sung Yeon, Yoon, Hee, Shin, Tae Gun, Sim, Min Seob, Jo, Ik Joon, Paeng, Hansol, Choi, Jong Soo, Cha, Won Chul
Publikováno v:
JMIR mHealth and uHealth, Vol 6, Iss 11, p e10666 (2018)
BackgroundThe task of monitoring and managing the entire emergency department (ED) is becoming more important due to increasing pressure on the ED. Recently, dashboards have received the spotlight as health information technology to support these tas
Externí odkaz:
https://doaj.org/article/eae6f8637a8c413c8aa9e956e67fedbd
Autor:
Yoon, Eunseop, Yoon, Hee Suk, Gowda, Dhananjaya, Eom, SooHwan, Kim, Daehyeok, Harvill, John, Gao, Heting, Hasegawa-Johnson, Mark, Kim, Chanwoo, Yoo, Chang D.
Text-to-Text Transfer Transformer (T5) has recently been considered for the Grapheme-to-Phoneme (G2P) transduction. As a follow-up, a tokenizer-free byte-level model based on T5 referred to as ByT5, recently gave promising results on word-level G2P c
Externí odkaz:
http://arxiv.org/abs/2308.08442